Outside ordering system

ABSTRACT

An ordering system for automated processing of customer orders for a retail establishment. In some embodiments, an ordering device is disposed at an ordering location such as outside a building of the retail establishment. The ordering device is configured to generate a first audio stream responsive to an interaction with an on-site customer adjacent the ordering device. An on-site controller device includes an artificial intelligence engine configured to generate content responsive to the first audio stream. The artificial intelligence engine combines the generated content with a second audio stream from an on-site employee to transmit a seamless third audio stream, via the ordering device, to the on-site customer. The generated content may be further tailored based on one or more traits of the customer as detected by a sensor.

RELATED APPLICATION

The present application is a continuation of co-pending U.S. patentapplication Ser. No. 17/496,425 filed Oct. 7, 2021, now issued as U.S.Pat. No. 11,594,223, the contents of which are hereby incorporated byreference.

SUMMARY

Assorted embodiments are directed to an ordering system optimized foroperation partially, or completely, outside a retail environment.

Without limitation, in some embodiments an apparatus is provided havingan ordering device disposed at an ordering location associated with aretail establishment. The ordering device is configured to generate afirst audio stream responsive to an interaction with an on-sitecustomer. An on-site controller device includes an artificialintelligence engine configured to generate content responsive to thefirst audio stream. The artificial intelligence engine combines thegenerated content with a second audio stream from an on-site employee totransmit a seamless third audio stream, via the ordering device, to theon-site customer.

In related embodiments, an ordering system is provided for processingcustomer orders for a retail establishment. The system includes anordering device disposed outside the retail establishment, and anon-site controller device. The controller device has an artificialintelligence engine configured to generate content responsive to a firstaudio stream from an on-site customer using the ordering device to placean order. The artificial intelligence engine combines the generatedcontent with a second audio stream from an on-site employee within theretail establishment to transmit a seamless third audio stream, via theordering device, to the on-site customer to confirm the order.

These and various other features and advantages which characterizevarious embodiments can be understood from the following detaileddescription in conjunction with a review of the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block representation of an example ordering environment inwhich various embodiments can be practiced.

FIG. 2 displays a block representation of an example orderingenvironment arranged in accordance with some embodiments.

FIG. 3 shows an example ordering system configured in accordance withassorted embodiments.

FIG. 4 illustrates a block representation of an example ordering modulethat can execute various embodiments of an ordering system.

FIG. 5 depicts portion of an example ordering system arranged andutilized in accordance with some embodiments.

FIG. 6 conveys a block representation of an example intelligence modulethat can be employed in assorted embodiments of an ordering system.

FIG. 7 is an example ordering routine that may be carried out withvarious embodiments of an ordering system.

DETAILED DESCRIPTION

Embodiments of the present disclosure are generally directed to anordering system that is optimized to incorporate artificial intelligenceand practical ordering optimizations into a retail environment wherecustomers are positioned outside.

In retail environments where ordering takes place outside, assorteddynamic conditions complicate the implementation of artificialintelligence. For instance, variable wind, customer position, andexternal sounds can inhibit the optimal performance of microphones thatcorrespond with input for artificial intelligence. The utilization ofhuman intervention with artificial intelligence ordering system is alsoriddled with complications, such as talking over a customer, missingportions of an order, or confusing the artificial intelligence engine.As such, there is a continued need for optimizations for orderingsystems employing artificial intelligence with customers positionedoutside a retail building.

In the example business environment 100 shown as a block representationin FIG. 1 , assorted embodiments of an intelligent ordering system canbe practiced. It is noted that the business environment 100 may compriseone or more retail, restaurant, and banking buildings that provide food,goods, and/or services for customers while the customer remains in avehicle. That is, the business environment 100 is configured to allow acustomer to remain in a vehicle while ordering a service/good/food andcontinuously until the service/good/food has been satisfied.

FIG. 1 depicts a block representation of portions of an example orderingenvironment 100 in which assorted embodiments can be practiced. Asshown, a single business is positioned on a site 102 and has at leastone building 104 outfitted to fulfill orders made by a customer 106,which is positioned outside the building 104, such as in a vehicle or onfoot. An outside ordering device 108 connects the customer 106 to ahuman employee 110.

With the advent of mobile computing and online ordering platforms, someembodiments involve the customer 106 communicating an order to theemployee 110 while other embodiments involve the customer 106 bypassingordering and instead simply picking up a completed order made online.Regardless of whether the human employee 110 communicates directly withthe customer 106, a customer's order prompts a work area 112, and thearea's constituent staff, into actions that satisfy the order(s).

Once an order has been satisfied, the customer 106 can receive theordered service/good/food via a drive-through pickup 114 or a deliveryservice by the human employee 110. It is noted that the work area 112 isnot limited to a particular activity, good, or service. Hence, the workarea 112 can consist of food preparation, banking operations, orpackaging of purchased goods without limitation.

The incorporation of an employee 110 into the ordering process, alongwith the difficulties inherent in outside ordering, such as wind andsub-optimal microphone placement relative to a customer, createcommunication difficulties that result in operational inefficiencies.For instance, inaccurate or incomplete orders from a customer 106 due tocommunication delays and/or degradation can frustrate the customer 106and cause general dissatisfaction with a retail establishment and lostprofits.

FIG. 2 depicts a block representation of another example orderingenvironment 120 that incorporates computing capabilities for takingoutside customer orders. Employing one or more computers 122 providesprocessing and memory that allows artificial intelligence, as well asother software, to be executed as part of a customer's order. Someembodiments activate and/or notify the computer 122 that a customer 106is present via one or more sensors 124, such as ultrasonic, inductive,pressure, ormagnetic vehicle devices.

While the computer 122 may operate independently to interact with acustomer 106, it is contemplated that a local employee 110 and/or remoteemployee 126 can suspend the artificial intelligence, bypass anycomputing/software, or temporarily pause less than all softwareexecution to interact directly with the customer 106. Despite theutilization of sophisticated computers 122, the suspension of artificialintelligence, or other software, to allow intervention of an employeecan be slow and add complexity to returning to software-based customerordering. That is, suspending software operation for an employee tocommunicate with a customer is wrought with operational difficulties inreturning to software-based ordering, which necessitates an employee toinefficiently finish an order with a customer if software is suspended.

With the possible involvement of artificial intelligence/softwareordering and employee interactions with customers, existing technologyhas failed to optimize the incorporation of local and/or remoteemployees with artificial intelligence order handling. Additionally,existing technology utilize a single audio stream shared by the customer106, employee 110, and artificial intelligence of a computer 122, whichis plagued by convoluted audio from different people that confuses theartificial intelligence, leads to delays, and causes incorrectintelligence translation of audio.

Accordingly, embodiments of an outside ordering system utilize dualaudio channels that allow for concurrent recording of customers 106 andemployees 110 that leads to accurate and efficient operation ofartificial intelligence to carry out an ordering operation from thecustomer 106.

FIG. 3 depicts a block representation of portions of an example orderingsystem 140 configured and operated in accordance with variousembodiments. A base station 142 can be connected inline between anordering device 144 and an employee 110, which can be physicallypositioned on-site or off-site. The base station 142 can provide somecomputing capabilities, such as vehicle detection via one or moreconnected sensors 124, wireless communications from the ordering device144 to/from an employee 110, and noise cancelling of verbal commandsfrom a customer 106. However, existing base stations 142 have limitedcomputing capabilities with respect to providing artificial intelligenceor optimizing the audio communications between customer 106 and employee110.

Accordingly, various embodiments connect a computing device 146 inlinebetween the base station 142 and employee 110 to complement thecapabilities of the base station 142 while optimizing ordering,communications, and delivery of artificial intelligence. The computingdevice 146 is configured to provide at least 4 separate audio inputchannels that can be individually modified, recorded, and amplified toincrease the clarity and timing of communications while conducting anorder as well as improve the accuracy of artificial intelligence inputand output.

As shown, output from one or more microphones is concurrently deliveredto the base station 142 and to the computing device 146. The dual audioinput to both the base station 142 and computing device 146 allow forsimultaneous analysis, recording, and optimizations. It is noted thatthe dual microphone inputs allow the computing device 146 to passivelyconduct artificial intelligence, audio adjustments, audio recording, andemployee 110 interactions. Meanwhile, the base station 142 can conductall normal activity with respect to vehicle detection and audiocommunications, but outputting to the computing device 146 instead ofdirectly to an employee 110. The capability of the computing device 146to provide dual concurrent audio streams allows for latency-free audiostreams between the customer 106 and employee 110 while providingartificial intelligence, audio recording, and audio parameteroptimization.

In accordance with some embodiments, the computing device 146 has anordering module 148 that intelligently monitors audio and outputs audioto the customer 106 with optimal timing and audio parameters. Thecomputing device 146 may also employ an intelligence module 150 thatexecutes artificial intelligence in response to detected and/orpredicted ordering aspects. The utilization of separate, concurrentaudio streams from the employee 110 and the customer 106 to thecomputing device 146 allows for strategic audio optimizations, such aspreamp, digital signal processing, and amplification alterations, whichprovides recorded and passthrough audio that is customized for clarity,accuracy, and timing. It is noted that by splitting audio streams, thecomputing device 146 can conduct artificial intelligence, along withother software, concurrently while audio recording and/or optimizationsare being conducted, which provides a seamless ordering experience tothe customer 106.

The multiple audio stream and intelligence capabilities of the computingdevice 146 further allows local and/or remote employee 110 interactionsdirectly with the computing device 146 without delaying, interrupting,or interfering with the execution of artificial intelligence orcommunications from a customer 106. Some embodiments utilize the basestation 142 to split portions of audio streams from the ordering device144 and/or employee 110, but such configuration is not required orlimiting. Employing the base station 142 to provide dynamic audio inputand/or output allows the computing device 146 to more efficientlyevaluate and optimize audio parameters, such as gain, processing,filtering, and noise cancelling, which allows for more processing to beutilized for artificial intelligence to operate and serve a customer106.

FIG. 4 depicts a block representation of an example ordering module 160configured in accordance with various embodiments to operate as part ofan ordering system. The module 160 can employ one or more controllers162, such as a microprocessor or other programmable circuitry, toevaluate and optimize audio parameters between a customer and anemployee. For instance, the controller 162 can determine if currentaudio parameters are optimal for a variety of criteria, such as customerposition relative to an ordering device, loudness of customer, windnoise, speed of customer ordering, customer accent, and customer gender.

As such, the controller 162 can determine if current ordering factorsare optimally served by current audio parameters, such as gain, noisereduction, and digital signal processing. If so, the controller 162 canprompt a switch circuit 164 to pass customer input to an employee and/orto an artificial intelligence engine. That is, the controller 162 andswitch circuit 164 can determine if customer audio is optimized forcurrent conditions and pass audio deemed clear, accurate, and notdelayed to an artificial intelligence engine. Conversely, the switchcircuit 164 can redirect customer audio to an employee or prompt thecustomer to repeat the order after audio parameters are customized toimprove clarity and/or accuracy.

The ordering module 160 may additionally have the capability todynamically control how audio streams are handled. A stream circuit 166,as shown, can direct the destination and/or recording of input data,audio, and commands from a remote source connected to the module 160 viaa wired and/or wireless connection, an on-site employee, an on-sitecustomer, and a remotely connected customer. The ability to identifyaudio, data, and command streams from different sources allows thestream circuit 166 to intelligently route audio to differentdestinations, record audio from different sources, and manipulate anaudio stream to splice multiple streams together. For instance, thestream circuit 166 can delay an audio stream from one source to preventinterference and/or confusion to a customer, employee, and artificialintelligence engine.

An analysis circuit 168 can operate with the module controller 162 toevaluate if optimal audio conditions are present for a customer,employee, and/or artificial intelligence engine. That is, the analysiscircuit 168 can detect current audio conditions, such as withenvironmental sensors, algorithms to determine audio characteristics ofa customer, and signal-to-noise metrics, to determine if one or moreamplification, filtering, or signal processing can improve the clarityand/or accuracy of an audio stream to optimize the customer's,employee's, or intelligence engine's understanding of what is beingsaid.

The analysis circuit 168 can suggest audio modifications to a singleaudio stream, which can create an employee audio stream that iscustomized for detected customer characteristics and/or customer audiothat is customized to be accurately interpreted by the artificialintelligence engine.

With the assorted circuitry, processing, and capabilities of theordering module 160, two or more audio ports of a computing device canbe utilized concurrently to evaluate and optimize audio streams as wellas pause, delay, and reorganize portions of audio streams to providecoherent and uninterrupted audio recordings and playback to an audiodestination. Despite the ability to optimize audio signals and streams,an outside ordering system can suffer from signal interference that candegrade audio stream clarity.

FIG. 5 depicts portions of an example outside ordering system 180arranged in accordance with various embodiments. An ordering device 182is physically positioned on a site and presents at least a microphone184 (MIC) to a customer to allow audio input and ordering. It iscontemplated that the ordering device 182 presents other orderingcomponents, such as a graphical interface, optical sensors, and staticdisplays.

A customer presence sensor 186 is positioned to detect the presence of acustomer and alert a base station 188. While the sensor 186 may havewireless connectivity, the use of wireless customer detection can bewrought with delay and unreliability. Hence, embodiments utilize a wiredconnection 190 from the sensor 186 to a base station 188. The wiredsensor connection 190 may be magnetically and/or electrically isolatedin an individual conduit, but such configuration can be inefficient interms of construction and maintenance. Accordingly, the wired connection190 extends to the base station 188, in some embodiments, in a commonconduit 192 as the electrical interconnections 194 for the variouscomponents of the ordering device 182.

It is noted that the physical proximity of the wired connection 190 withthe interconnections 194 in the common conduit 192 can introduceinterference, particularly with audio signals that are amplified and/orotherwise digitally processed. That is, the physical configuration ofthe wired connection 190 can jeopardize the accuracy and/or timing ofdetecting customers when positioned proximal other electricalinterconnections, such as connections carrying amplified audio signals.

For these reasons, a computing device 146 can customize audio signalsbetween the ordering device 182 and the base station 188 to notinterfere, or otherwise degrade, operation of the wired connection 190to detect the presence of a customer. While not limiting or required,audio signal customizations can be complemented by electrical components196, such as capacitors, resistors, and filter, to limit transientsignals that can interfere with the operation of the wired connection190. It is contemplated that the computing device 146 can customizeaudio signals at selected times until initial customer detection andsubsequently suspend audio signal customization to prevent sensor 186interference, which allows any physically present electrical components196 to condition the customer presence signals.

FIG. 6 conveys a block representation of an example intelligence module200 that can be utilized in an outside ordering system in accordancewith some embodiments. It is noted, but not required, that theintelligence module 200 employs the same controller 162, or otherprocessing capability, as the ordering module 160. However, a specificcontroller is not required as different circuitry of the intelligencemodule 200 can be programmable and provide capability to interpret inputinformation, such as customer identification, customer detectedcharacteristics, environmental information, voice characteristics, anddigital order aspects, to create at least a customer strategy andtriggers to direct order handling to an artificial intelligence engine202 or an employee.

The artificial intelligence engine 202 has at least a speech-to-textcircuit 204 and a text-to-speech circuit 206 that are operated by anorder processor 208 to carry out automated customer interactions. Thatis, the order processor 208 can translate a customer's audio into textthat can be analyzed and interpreted into a retail order as well asconvert text generated by the order processor 208, such as ordersuggestions from an upsell circuit 210, into speech that is relayed to acustomer. It is contemplated that the intelligence engine 202communicates with a customer and/or employee via text only, but suchconfiguration is not required.

The upsell circuit 210 can take a variety of factors into accountunrelated to the customer, such as time of day, weather, employeeefficiency, employee availability, and location, and may also take intoaccount information about the relative position of an order. Forinstance, if a customer has ordered burgers and a fry try to upsell adrink to make it a combo.

Regardless how the intelligence engine 202 communicates, the ability toascertain characteristics about a customer, such as by identifying anexisting customer profile, customer vehicle type, customer accent,customer gender, and customer mood, allows the upsell circuit 210 togenerate one or more unprompted suggestions to the customer that can beinjected into an audio stream without delaying, interrupting, orinterfering with the audio stream by the ordering module 160.

The use of dual audio ports in the computing device 146 employing theintelligence module 200 allows an employee to interact directly with theintelligence engine 202 without interrupting or delaying a customer'sorder that is concurrently taken and recorded on a separate audio port.An alteration circuit 212 allows the a local, or remote, employee toseamlessly make changes to the operation of the intelligence module 200without interfering with the customer's order or delaying theintelligence engine's 202 interactions with the customer.

Through the autonomous operation of the intelligence engine 202 to takeand satisfy customer orders, the intelligence module 200 can providehighly efficient retail transactions and customer throughput. Theability for an employee to communicate with the intelligence engine 202directly and without interrupting a customer's order allows forstrategic modifications to how the engine 202 operates, the orders theengine 202 generates, and/or the upsell options selected by the engine202.

Some embodiments allow for the employee to inject a personal,non-computer generated, text, audio snippet, or sound to the engine'sinteraction with a customer. That is, the intelligence module 200 canincorporate input from an employee that is seamlessly installed in anaudio stream from the module 200 to the customer without degrading theinput customer stream due to the use of multiple concurrent audiochannels dedicated to customer/employee/intelligence engine operation.

The use of multiple independent audio channels for operation of anordering system further allows the intelligence module 200 to recordvarious aspects of encountered audio from customers and employees, whichprovides opportunities to separately analyze and learn how the automatedinteractions between the intelligence engine 202 and the customer can beimproved. For instance, the intelligence engine 202 can employ machinelearning and/or table based correlations on recorded employee and/orcustomer audio streams to develop and evolve interactions with customersto increase the satisfaction, efficiency, and profitability of automatedordering.

The ability to analyze separate customer and employee audio streams inrealtime and recorded formats allows the intelligence module 200 togenerate one or more customer strategies that prescribe alterations fromdefault ordering parameters in response to detected, or predicted,triggers.

A non-limiting example of a customer strategy prescribes differentartificial intelligence themes, responses, timing, and/or tone inresponse to customer traits, such as gender, type of vehicle, type ofapparel worn, age, facial gestures, volume, and hair style, detectedfrom one or more optical and/or acoustic sensors. For example, theintelligence module 200 can proactively generate multiple differentcustomer strategies that are executed when a customer trigger isdetected, such as modifying the tone and timing of automatedinteractions in response to detecting the customer is an older aged ladyor young man.

Another example involves changing from a strict ordering protocol to aconversational protocol with the automated customer interactions, asgenerated by the intelligence engine 202, in response to detection of aminivan or sport utility vehicle. Such conversational protocol mayinvolve predetermined, or spontaneous, customer questions and subsequentfollow up responses from the intelligence engine 202 while the strictordering protocol may involve no questions or responses other than whatis needed to complete an order.

It is contemplated that the customer strategy can prescribe differentupsell tactics in response to predetermined triggers. For instance,detection of a man within a demographic range of age and ethnicity canprompt a first set of upsell suggestions for the automated intelligenceinteractions while a woman driving a sports car may prompt a differentsecond set of upsell suggestions. It is noted that upsell suggestionsmay involve asking a customer if they want a different, modified, oradditional order item.

A customer strategy may involve alterations to operational parameters inresponse to detected, or predicted, triggers. For example, detection ofan elevated tone or timing for a customer can prompt recording customercommands and slowing the playback for the intelligence engine 202 and/oremployee. Other dynamic operational parameters may involve alteringaudio stream amplification, routing, filtering, and/or signal processingin response to detection or prediction of degraded audio conditions,such as wind, customer location relative to a microphone array, lowsignal quality, or high signal noise.

The proactive generation of the customer strategy and triggers allowsthe intelligence module 200 and ordering module 160 to efficiently alterfrom default ordering parameters to provide optimal audio quality and/orautomated artificial intelligence interactions that promote customersatisfaction and/or profitability. In contrast, reactively modifyingordering parameters and/or automated interactions can involve delaysthat frustrate a customer's ordering experience. It is noted that asingle system can position the intelligence module 200 either on asingle site or in the cloud while being separate from the orderingmodule 160.

FIG. 7 depicts an example ordering routine 220 that can be carried outwith the assorted embodiments of FIGS. 1-6 . While not limiting orrequired, step 222 detects a vehicle with a customer presence sensor andprompts a base station to initiate an ordering sequence. The basestation then notifies an on-site computing device of a customer, whichcauses default ordering parameters and intelligence to be loaded in step224. The default condition allows an order to be initiated via automatedintelligence or an employee as customer traits are evaluated in step226. That is, a default condition can have a human employee greet acustomer or execute an automated greeting via the intelligence modulewhile step 226 is conducted.

The evaluation of customer traits can involve one or more sensors, suchas optical, acoustic, or ultrasonic detectors, measuring static and/ordynamic aspects of a customer, the customer's car, and customer'sspeech. Customer traits may prompt the prediction of other orderingaspects, such as ordering speed, volume, and interest in conversationunrelated to an order.

The evaluated customer traits allow an intelligence module to generate,or select a preexisting, customer strategy in step 228 that customizesaudio parameters and/or automated order intelligence protocol toincrease the efficiency, satisfaction, and profitability of an orderprocess. It is noted that step 228 can correspond with one or moretriggers that prompt automated, or employee, alterations to audio and/orautomated order interactions.

The creation, or selection, of a customer strategy allows decision 230to determine if a trigger is reached, or is predicted to be reached.Hence, an ordering system can employ circuitry that accurately predictsfuture customer behavior, audio characteristics, and upsell suggestionsuccess from prior logged customer interactions, model data, and/orprediction algorithms executed on the on-site computing device.

If decision 230 detects, or predicts, a trigger being reached, step 232changes one or more ordering aspects in accordance with the customerstrategy. While not limiting, step 232 can utilize the dual audio portsto modify the amplification, filtering, application of digital signalprocessing, and filtering of an audio stream to, or from, a customer aswell as modify how automated intelligence is interacting with acustomer, such as speed, tone, or volume of an audio stream to acustomer.

Although an employee can communicate directly with the intelligenceengine carrying out automated order taking, a customer strategy canprescribe trigger events when an employee is needed to supplementautomated order taking. Decision 234 evaluates if such an employeetrigger is imminent. If so, step 236 seamlessly injects a recordedmessage or a real-time communication pathway to a customer. The multipleaudio ports of the on-site computing device allows step 236 to spliceemployee audio with customer and artificial intelligence audio streamswithout introducing delay, confusion, or interference.

At any point during interaction with a customer, decision 238 canevaluate is an upsell opportunity is present. Some embodiments consultthe customer strategy to determine the chance an upsell is successfuland initiates the upsell of one or more items in step 240 if the successchance is above a predetermined threshold, such as 50% or 90%. Thus, anon-site computing device can continuously, sporadically, or routinely,compute the chance of a successful upsell based on previously loggedcustomer behavior, model data, executed algorithms, and employee input,which allows for the identification of upsell opportunities whilepreventing an upsell attempt when there exists a small chance ofsuccess.

At the conclusion of an order and/or interactions with a customer, step242 evaluates the recorded audio streams from the customer, intelligencemodule, and employee to determine if the selected customer strategyprovided the optimal ordering conditions, if the customer strategy canbe altered to improve the quality of an ordering process, or if atrigger can be altered to increase the efficiency or profitability of afuture order from a customer exhibiting similar traits.

It is noted that any number of audio streams can be combined into otheraudio streams, such as two streams combining into one stream transmittedto, or from, a customer. Various embodiments can concurrently outputmultiple different audio streams without combining any streams whileother embodiments combine less than all audio streams to create acustomized audio delivery to the computing device, a customer, or anemployee, depending on need for the system. While it is contemplatedthat customers remain in vehicles when ordering, such configuration isnot required or limiting as a customer can be outside a vehicle, insidea building, or outside a building.

Through the utilization of an on-site computing device with multipleaudio ports, customer, employee, and automated intelligence can utilizeindependent audio streams that can be optimized to improve the orderingexperience for the customer.

Some embodiments split inbound microphone audio signals from a customerto a base station and the on-site computing device. Audio streams can beoptimized with dynamic preamplification, amplification, filtering, anddigital signal processing. The multiple audio streams allows an employeeto communicate directly with artificial intelligence that conductsautomated order taking without delaying, interrupting, or otherwiseconvoluting the audio stream to/from the customer. The multiple audiostreams and computing capabilities of the on-site computing deviceallows for multiple lanes of a drive-thru retail environment to beconcurrently operating while optimized audio signals can preventinterference with wired customer presence sensors.

What is claimed is:
 1. An apparatus comprising: an ordering devicedisposed at an ordering location associated with a retail establishmentand configured to generate a first audio stream responsive to aninteraction with an on-site customer; and an on-site controller devicecomprising an artificial intelligence engine configured to generatecontent responsive to the first audio stream and to combine thegenerated content with a second audio stream from an on-site employee totransmit a seamless third audio stream, via the ordering device, to theon-site customer.
 2. The apparatus of claim 1, wherein the on-sitecontroller device concurrently receives the first audio stream from theordering device and the second audio stream from the on-site employee.3. The apparatus of claim 1, wherein the on-site controller devicegenerates the content responsive to the first audio stream by slowingplayback of the first audio stream to interact with the artificialintelligence engine of the on-site computing device.
 4. The apparatus ofclaim 1, wherein the on-site controller device generates the contentresponsive to the first audio stream by detecting at least one traitassociated with the customer using a sensor of the ordering device. 5.The apparatus of claim 1, wherein the artificial intelligence enginecomprises a speech-to-text circuit configured to convert the first audiostream to a first set of text, a text generator circuit configured togenerate a second set of text responsive to the first set of text, and atext-to-speech circuit configured to generate the content as audiblespeech for incorporation into the third audio stream corresponding tothe generated second set of text.
 6. The apparatus of claim 5, whereinthe second set of text corresponds to a request to add one or moreadditional items to an order placed by the on-site customer in the firstaudio stream.
 7. The apparatus of claim 1, wherein the controller devicefurther comprises a memory in which the first audio stream and thesecond audio stream while the on-site controller device executes anautomated ordering process with the customer via the ordering device. 8.The apparatus of claim 1, wherein the ordering device is a firstordering device and the on-site customer is a first on-site customer,wherein the apparatus further comprises a second ordering deviceconcurrently communicating with a second on-site customer to generate afourth audio stream, and wherein the on-site controller device uses theartificial intelligence engine to generate different, second contentresponsive to the fourth audio stream and transmits the second content,via the second ordering device, to the second on-site customerconcurrently with the transmission of the third audio stream to thefirst on-site customer.
 9. The apparatus of claim 8, wherein the on-sitecontroller device concurrently conducts automated ordering processes foreach of the first and second on-site customers.
 10. The apparatus ofclaim 8, wherein the on-site controller device induces a delay in thefourth audio stream from the second on-site customer to enable theon-site employee to successively generate and output the second audiostream for the first on-site customer followed by a fifth audio streamfor the second on-site customer.
 11. The apparatus of claim 1, whereinthe on-site controller device is further configured to generate acustomer strategy to direct automated interactions between theartificial intelligence engine and the first on-site customer to compilea retail order, the automated interactions involving the artificialintelligence engine generating new and unique text to converse with thefirst on-site customer responsive to the first audio stream, convertingthe text to speech, and relaying the speech to the on-site customer viathe ordering device.
 12. An ordering system for processing customerorders for a retail establishment, comprising: an ordering devicedisposed outside the retail establishment; and an on-site controllerdevice comprising an artificial intelligence engine configured togenerate content responsive to a first audio stream from an on-sitecustomer using the ordering device to place an order, and to combine thegenerated content with a second audio stream from an on-site employeewithin the retail establishment to transmit a seamless third audiostream, via the ordering device, to the on-site customer to confirm theorder.
 13. The ordering system of claim 12, further comprising acustomer sensor adjacent the ordering device configured to detect andtransmit at least one customer trait associated with the on-sitecustomer to the on-site controller device, wherein the artificialintelligence engine further generates the generated content responsiveto the at least one customer trait from the customer sensor.
 14. Theordering system of claim 12, wherein the on-site controller deviceconcurrently receives the first audio stream from the ordering deviceand the second audio stream from the on-site employee.
 15. The orderingsystem of claim 12, wherein the on-site controller device generates thecontent responsive to the first audio stream by slowing playback of thefirst audio stream to interact with the artificial intelligence engineof the on-site computing device.
 16. The ordering system of claim 12,wherein the artificial intelligence engine comprises a speech-to-textcircuit configured to convert the first audio stream to a first set oftext, a text generator circuit configured to generate a second set oftext responsive to the first set of text, and a text-to-speech circuitconfigured to generate the content as audible speech for incorporationinto the third audio stream corresponding to the generated second set oftext.
 17. The ordering system of claim 16, wherein the second set oftext corresponds to a request to add one or more additional items to anorder placed by the on-site customer in the first audio stream.
 18. Theordering system of claim 12, wherein the controller device furthercomprises a memory in which the first audio stream and the second audiostream while the on-site controller device executes an automatedordering process with the customer via the ordering device.
 19. Theordering system of claim 12, wherein the ordering device is a firstordering device and the on-site customer is a first on-site customer,wherein the apparatus further comprises a second ordering deviceconcurrently communicating with a second on-site customer to generate afourth audio stream, and wherein the on-site controller device uses theartificial intelligence engine to generate different, second contentresponsive to the fourth audio stream and transmits the second content,via the second ordering device, to the second on-site customerconcurrently with the transmission of the third audio stream to thefirst on-site customer.
 20. The ordering system of claim 12, wherein theon-site controller device is further configured to generate a customerstrategy to direct automated interactions between the artificialintelligence engine and the first on-site customer to compile a retailorder, the automated interactions involving the artificial intelligenceengine generating new and unique text to converse with the first on-sitecustomer responsive to the first audio stream, converting the text tospeech, and relaying the speech to the on-site customer via the orderingdevice.